This paper revisits a number of data-rich prediction methods, like factor models, Bayesian ridge regression and forecast combinations, which are widely used in macroeconomic forecasting, and compares these with a lesser known alternative method: partial least squares regression. Under the...

We compare a number of data-rich prediction methods that are widely used in macroeconomic forecasting with a lesser known alternative: partial least squares (PLS) regression. In this method, linear, orthogonal combinations of a large number of predictor variables are constructed such that the...

Several Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time series....

Several Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time series....

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

We reassess the predictability of U.S. recessions at horizons from three months to two years ahead for a large number of previously proposed leading-indicator variables. We employ an efficient probit estimator for partially missing data and assess relative model performance based on the receiver...

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

We reassess the predictability of U.S. recessions at horizons from three months to two years ahead for a large number of previously proposed leading-indicator variables. We employ an efficient probit estimator for partially missing data and assess relative model performance based on the receiver...

Today, the problem facing the United States is not whether cryptocurrencies are money or “thin air,” Iran's nuclear ambition, or COVID-19 induced recession; it is China's fast acceleration in becoming a game changer in the world order that the U.S. has dominated for more than a century....

Over the past two decades, U.S. core PCE goods and services inflation have evolved differently. Against the backdrop of global concerns of low inflation, we use this trend as motivation to develop a bottom-up model of U.S. inflation. We find that domestic forces play a larger role relative to...